This book gathers together much of the author’s work – both old and new - to explore a number of the key increases in complexity seen in the natural world, seeking to explain each of them purely in terms of the features of fitness landscapes. In a very straightforward manner, the book introduces basic concepts to help readers follow the main ideas. By using variations of the NK model and including the concept of the Baldwin effect, the author presents new abstract models that are able to explain why sources of evolutionary innovation (genomes, symbiosis, sex, chromosomes, multicellularity) have been selected for and hence how complexity has increased over time in some lineages.
This book gathers together much of the author’s work – both old and new - to explore a number of the key increases in complexity seen in the natural world, seeking to explain each of them purely in terms of the features of fitness landscapes. In a very straightforward manner, the book introduces basic concepts to help readers follow the main ideas. By using variations of the NK model and including the concept of the Baldwin effect, the author presents new abstract models that are able to explain why sources of evolutionary innovation (genomes, symbiosis, sex, chromosomes, multicellularity) have been selected for and hence how complexity has increased over time in some lineages.
Larry Bull
Evolutionary Innovation Baldwin Effect Landscape Ruggedness Fitness Landscape Models Evolution of Sex Evolution of Genome Length Evolution of Multicellularity Evolution of Symbiosis NK Model NKCS Model Evolution of Mating Types Model of Coevolution Emergence of Dominance Evolution of Sex Chromosomes Symbiogenesis
“This book offers an excellent entry point for newcomers to research ... . the reader learns about a wide range of fascinating open questions regarding the evolution of complexity. I was truly impressed at the variety of concepts that were touched on. Ultimately, I could absolutely imagine giving this to a new student as a quick introduction to this flavor of research, and I very much enjoyed reading it myself too!” (Emily Dolson, Genetic Programming and Evolvable Machines, Vol. 23 (4), 2022)
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